Blood‐brain barrier dysfunction in canine epileptic seizures detected by dynamic contrast‐enhanced magnetic resonance imaging
Bibliographic record
Abstract
OBJECTIVE: Dogs with spontaneous or acquired epilepsy exhibit resemblance in etiology and disease course to humans, potentially offering a translational model of the human disease. Blood-brain barrier dysfunction (BBBD) has been shown to partake in epileptogenesis in experimental models of epilepsy. To test the hypothesis that BBBD can be detected in dogs with naturally occurring seizures, we developed a linear dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) analysis algorithm that was validated in clinical cases of seizing dogs and experimental epileptic rats. METHODS: Forty-six dogs with naturally occurring seizures of different etiologies and 12 induced epilepsy rats were imaged using DCE-MRI. Six healthy dogs and 12 naive rats served as control. DCE-MRI was analyzed by linear-dynamic method. BBBD scores were calculated in whole brain and in specific brain regions. Immunofluorescence analysis for transforming growth factor beta (TGF-β) pathway proteins was performed on the piriform cortex of epileptic dogs. RESULTS: We found BBBD in 37% of dogs with seizures. A significantly higher cerebrospinal fluid to serum albumin ratio was found in dogs with BBBD relative to dogs with intact blood-brain barrier (BBB). A significant difference was found between epileptic and control rats when BBBD scores were calculated for the piriform cortex at 48 hours and 1 month after status epilepticus. Mean BBBD score of the piriform lobe in idiopathic epilepsy (IE) dogs was significantly higher compared to control. Immunohistochemistry results suggested active TGF-β signaling and neuroinflammation in the piriform cortex of dogs with IE, showing increased levels of serum albumin colocalized with glial acidic fibrillary protein and pSMAD2 in an area where BBBD had been detected by linear DCE-MRI. SIGNIFICANCE: Detection of BBBD in dogs with naturally occurring epilepsy provides the ground for future studies for evaluation of novel treatment targeting the disrupted BBB. The involvement of the piriform lobe seen using our linear DCE-MRI protocol and algorithm emphasizes the possibility of using dogs as a translational model for the human disease.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".